Abstract


13:00〜14:00

Tutorial 1:
An Introduction to Computational Organization Theory
-From Basic theory of Social Simulation to Recent Studies-
Keiki Takadama(ATR)

Abstract:
This paper focuses on "computational organization theory" (COT) and
introduces its overview by referring Carley's papers [Carley, 1995;
Carley and Gasser, 1999]. Through an introduction to COT, this paper
aims to summarize issues from basic parts of social simulation to
recent studies in COT area. In particular, this paper explains why COT
is currently attracted in organizational science, describes the
modeling of organizations, and summarizes the current research issues
and famous conventional models in COT ares.

14:00〜15:00

Tutorial 2:
Complex Reflexive Agents as Models of Social Actors
Peter Dittrich (University of Dortmund)

Abstract:
The first part of the talk gives an overview about the socionics initiative which has been established by the German Research Foundation (DFG) about three years ago. In this initiative eight project cooperating in a tandem-structure with at least one partner from Computer Science and one from Sociology in each "tandem project". Socionics aims on the one hand at developing computer technologies by employing paradigms of our social world, on the other hand computer science techniques are used to develop and validate social theories. A third aspect of socionics is the study of hybrid systems which consist of real social actors (e.g., humans) and artificial actors (e.g., software agents). The second part of the talk focuses on our own project where the central metaphor is "the complex agent". I will present latest results from two lines of research we are following:

(1) An architecture to build ``realistic'' agents for modeling social actors.
This architecture allows to integrate different actor models, such as the homo sociologicus or the  homo economics (rational man), and to switch  between these models smoothly.

(2) Models of learning and reflexive agents.
An important aspect of  "realistic" agents as models of social actors is their ability to predict the behavior of their environment, to learn, and to consider that their own action is predicted by other actors (reflexivity). In this line of research we have developed a model which uses genetic programming (GP) as a learning mechanism, and a model of the "situation of double contingency" introduced by Luhmann as an explanation for the origin of social order where learning and reflexivity plays an important role.


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